Master Thesis - 3D Point Cloud Segmentation with web-scale Foundation Models
Why This Matters
Perception systems in autonomous vehicles rely on accurate 3D representations of the surrounding environment. While deep learning methods have advanced this capability, they still demand vast amounts of annotated data for training. Vision-language foundation models have gained significant attention recently due to their ability to leverage the vast amount of data available on the internet through self-supervised training. These models have proven to be effective in many 2D vision tasks. However, applying these models to 3D tasks, such as those involving autonomous driving, presents new challenges and opportunities for further exploration.
Your Role in the Project
In this master thesis project, you will:
- Investigate methods for distilling knowledge from vision-language foundation models.
- Apply these methods to create automatic labels for training neural networks to segment 3D Lidar and Radar point clouds.
- Test and evaluate the resulting models on Zenseact's open dataset.
What We’re Looking For
We are seeking one or two motivated students with:
- A strong foundation in mathematics (statistical analysis, linear algebra, probability theory, etc.).
- Experience in deep learning and sensor fusion.
- Proficiency in Python programming.
What’s in it for You?
- Hands-on Experience: You'll work on state-of-the-art technologies in the autonomous driving domain.
- Skill Development: Expand your expertise in 3D sensor data, self-supervised learning, and neural networks.
- Industry Collaboration: Collaborate with Zenseact's innovative team, gaining real-world insights into AI applications in autonomous vehicles.
- Career Growth: This project will enhance your skills and prepare you for cutting-edge roles in AI, deep learning, and autonomous systems.
How to Apply & Important Details
This is a project suitable for one or two people, and we prefer that you apply with a partner who complements your skill set. However, individual applications are welcome.
- Planned start: January 2025, with flexibility.
- Final application date: November 15, 2024 (applications are reviewed on an ongoing basis).
- Duration: 30 ECTS.
Please submit individual applications, including your CV, motivational letter, and grade transcripts. If you are applying with a partner, mention this in your application.For questions regarding the project, please contact Maryam Fatemi at maryam.fatemi@zenseact.com and Willem Verbeke at willem.verbeke@zenseact.com.
More about Zenseact
Our software makes a difference.
Using AI-based technology to create the ultimate driver support, we’re fighting to end car accidents and make roads safe for everyone. Around 1,4 million people die in traffic yearly while approximately 50 million people get injured. Many get disabled as a result of their injury. We can do better.
One purpose, one product.
We’re a software company dedicated to revolutionizing car safety. By designing the complete software stack for autonomous driving and advanced driver-assistance systems, we’re fighting to end car accidents and make roads safe for everyone. Zenseact was founded by Volvo Cars, and the teams are based in Gothenburg, Sweden, and Shanghai, China.When we aim for zero accidents faster, we strive to speed up the transition to safe automation. This is essentially achieved by making cars updatable – like a computer or a phone. With regular software updates, a vehicle can be made safer long after its production. By accelerating improvement loops, shortening development cycles, and deploying high-capacity software quickly, we can make cars safer, faster.
Culture with people at heart
To achieve our mission of saving lives and ending traffic accidents is to go where nobody has before. It requires us to venture into the unknown, pioneering new technology and pushing the frontier of autonomous driving. While there’s no denying our determination and expertise, we must stand united to succeed. By fostering a culture of support and enablement – a place of psychological safety where all of us can thrive – everything else will follow. We call this a people-at-heart culture. This culture means caring. It means the company cares about me, and we care about one another. It means sharing, so we give each other energy and have fun together. Our culture is also about belonging. It’s important to feel at home and that we can be ourselves at work. Finally, a people-at-heart culture means well-being. So, we enjoy the flexibility needed to be and do our best – at work and in life.
Zenseact works proactively to create a culture of diversity and inclusion, where individual differences are appreciated and respected. To drive innovation we see diversity as an asset, which means we value and respect differences in gender, race, ethnicity, religion or other belief, disability, sexual orientation or age etc.
Interviews are held on a continuous basis, so we highly recommend that you submit your application at your earliest convenience.
- Competence area
- Opportunities for Students, Graduates & Innovators
- Locations
- Gothenburg, Sweden
- Remote status
- Hybrid
Gothenburg, Sweden
About Zenseact
One purpose, one product
We are a software company focused on transforming car safety. By developing a complete software stack for autonomous driving and advanced driver-assistance systems, we aim to eliminate car accidents and make roads safer for all. Founded by Volvo Cars, Zenseact operates globally, with teams in Gothenburg and Lund, Sweden; Munich, Germany; and Shanghai, China.
Master Thesis - 3D Point Cloud Segmentation with web-scale Foundation Models
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